Transfer learning method and transfer learning system for large-scale data calibration

Transfer learning method and transfer learning system for large-scale data calibration

  • CN 106,599,922 A
  • Filed: 12/16/2016
  • Published: 04/26/2017
  • Est. Priority Date: N/A
  • Status: Active Grant
First Claim
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1. a kind of transfer learning method, including:

  • Step a) is using at least two graders based on the source domain data training demarcated respectively to aiming field number to be calibratedAccording to being demarcated, the calibration result identical target numeric field data of at least two graders is added to into Candidate Set, remaining aiming fieldData constitute remaining part;

    Data are grouped by its demarcation, will be had for the target numeric field data of source domain data and Candidate Set by step b) respectivelyThe source domain data set and aiming field data set of identical demarcation is converted into the source domain data set after the same space causes to convert and targetNumeric field data group meets same distribution, and each source domain data set obtained after conversion and aiming field data set are distinguished merger Cheng XinyuanDomain and new Candidate Set;

    Step c) is demarcated to the target numeric field data in new Candidate Set based on the grader trained in new source domain, and using newIn Candidate Set, the calibration result of each data updates the demarcation to each data in not transformed Candidate Set;

    Step d) trains grader based on calibrated Candidate Set is updated over, and is completed to number of targets in remaining part using the graderAccording to demarcation.

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